Local Granger causality

Granger causality (GC) is a statistical notion of causal influence based on prediction via linear vector autoregression. For Gaussian variables it is equivalent to transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes. We exploit such equivalence and calculate exactly the local Granger causality, i.e., the profile of the information transferred from the driver to the target process at each discrete time point; in this frame, GC is the average of its local version. We show that the variability of the local GC around its mean relates to the interplay between driver and innovation (autoregressive noise) processes, and it may reveal transient instances of information transfer not detectable from its average values. Our approach offers a robust and computationally fast method to follow the information transfer along the time history of linear stochastic processes, as well as of nonlinear complex systems studied in the Gaussian approximation

Gradients of O-information highlight synergy and redundancy in physiological applications

The study of high order dependencies in complex systems has recently led to the introduction of statistical synergy, a novel quantity corresponding to a form of emergence in which patterns at large scales are not traceable from lower scales. As a consequence, several works in the last years dealt with the synergy and its counterpart, the redundancy. In particular, the O-information is a signed metric that measures the balance between redundant and synergistic statistical dependencies. In spite of its growing use, this metric does not provide insight about the role played by low-order scales in the formation of high order effects. To fill this gap, the framework for the computation of the O-information has been recently expanded introducing the so-called gradients of this metric, which measure the irreducible contribution of a variable (or a group of variables) to the high order informational circuits of a system. Here, we review the theory behind the O-information and its gradients and present the potential of these concepts in the field of network physiology, showing two new applications relevant to brain functional connectivity probed via functional resonance imaging and physiological interactions among the variability of heart rate, arterial pressure, respiration and cerebral blood flow

Synergistic information transfer in the global system of financial markets

Uncovering dynamic information flow between stock market indices has been the topic of several studies which exploited the notion of transfer entropy or Granger causality, its linear version. The output of the transfer entropy approach is a directed weighted graph measuring the information about the future state of each target provided by the knowledge of the state of each driving stock market index. In order to go beyond the pairwise description of the information flow, thus looking at higher order informational circuits, here we apply the partial information decomposition to triplets consisting of a pair of driving markets (belonging to America or Europe) and a target market in Asia. Our analysis, on daily data recorded during the years 2000 to 2019, allows the identification of the synergistic information that a pair of drivers carry about the target. By studying the influence of the closing returns of drivers on the subsequent overnight changes of target indexes, we find that (i) Korea, Tokyo, Hong Kong, and Singapore are, in order, the most influenced Asian markets; (ii) US indices SP500 and Russell are the strongest drivers with respect to the bivariate Granger causality; and (iii) concerning higher order effects, pairs of European and American stock market indices play a major role as the most synergetic three-variables circuits. Our results show that the Synergy, a proxy of higher order predictive information flow rooted in information theory, provides details that are complementary to those obtained from bivariate and global Granger causality, and can thus be used to get a better characterization of the global financial system

Regressing multiple viral plaques and skin fragility syndrome in a cat coinfected with FcaPV2 and FcaPV3

Feline viral plaques are uncommon skin lesions clinically characterized by multiple, often pigmented, and slightly raised lesions. Numerous reports suggest that papillomaviruses (PVs) are involved in their development. Immunosuppressed and immunocompetent cats are both affected, the biological behavior is variable, and the regression is possible but rarely documented. Here we report a case of a FIV-positive cat with skin fragility syndrome and regressing multiple viral plaques in which the contemporary presence of two PV types (FcaPV2 and FcaPV3) was demonstrated by combining a quantitative molecular approach to histopathology. The cat, under glucocorticoid therapy for stomatitis and pruritus, developed skin fragility and numerous grouped slightly raised nonulcerated pigmented macules and plaques with histological features of epidermal thickness, mild dysplasia, and presence of koilocytes. Absolute quantification of the viral DNA copies (4555 copies/microliter of FcaPV2 and 8655 copies/microliter of FcaPV3) was obtained. Eighteen months after discontinuation of glucocorticoid therapy skin fragility and viral plaques had resolved.The role of the two viruses cannot be established and it remains undetermined how each of the viruses has contributed to the onset of VP; the spontaneous remission of skin lesions might have been induced by FIV status change over time due to glucocorticoid withdraw and by glucocorticoids withdraw itself

Numerical simulations of compressible Rayleigh-Taylor turbulence in stratified fluids

We present results from numerical simulations of Rayleigh-Taylor turbulence, performed using a recently proposed lattice Boltzmann method able to describe consistently a thermal compressible flow subject to an external forcing. The method allowed us to study the system both in the nearly-Boussinesq and strongly compressible regimes. Moreover, we show that when the stratification is important, the presence of the adiabatic gradient causes the arrest of the mixing process.Comment: 15 pages, 11 figures. Proceedings of II Conference on Turbulent Mixing and Beyond (TMB-2009

Turbulent pair dispersion of inertial particles

The relative dispersion of pairs of inertial particles in incompressible, homogeneous, and isotropic turbulence is studied by means of direct numerical simulations at two values of the Taylor-scale Reynolds number $Re_{\lambda} \sim 200$ and 400. The evolution of both heavy and light particle pairs is analysed at varying the particle Stokes number and the fluid-to-particle density ratio. For heavy particles, it is found that turbulent dispersion is schematically governed by two temporal regimes. The first is dominated by the presence, at large Stokes numbers, of small-scale caustics in the particle velocity statistics, and it lasts until heavy particle velocities have relaxed towards the underlying flow velocities. At such large scales, a second regime starts where heavy particles separate as tracers particles would do. As a consequence, at increasing inertia, a larger transient stage is observed, and the Richardson diffusion of simple tracers is recovered only at large times and large scales. These features also arise from a statistical closure of the equation of motion for heavy particle separation that is proposed, and which is supported by the numerical results. In the case of light particles with high density ratios, strong small-scale clustering leads to a considerable fraction of pairs that do not separate at all, although the mean separation increases with time. This effect strongly alters the shape of the probability density function of light particle separations.Comment: 28 pages, 15 figure

Bovine papillomavirus 1 gets out of the flock: Detection in an ovine wart in Sicily

A proliferative cauliflower lesion was excised from the udder of a sheep. Histological investigation confirmed the macroscopic classification of the lesion as a papilloma, without any fibroblastic proliferation. PCR revealed the presence of bovine papillomavirus (BPV), which was further confirmed by the identification of a Deltapapillomavirus 4 by Next Generation Sequencing analysis. This was subsequently classified as bovine papillomavirus type 1. Negative staining electron microscopy (EM) analyses produced negative test results for papillomavirus particles. RNA in situ hybridization (ISH) confirmed the presence of BPV-1. The results further confirm the ability of BPVs belonging to the Deltapapillomavirus genus to infect distantly related species and to cause lesions that are different from sarcoids

Mesoscopic model for soft flowing systems with tunable viscosity ratio

We propose a mesoscopic model of binary fluid mixtures with tunable viscosity ratio based on a two-range pseudopotential lattice Boltzmann method, for the simulation of soft flowing systems. In addition to the short-range repulsive interaction between species in the classical single-range model, a competing mechanism between the short-range attractive and midrange repulsive interactions is imposed within each species. Besides extending the range of attainable surface tension as compared with the single-range model, the proposed scheme is also shown to achieve a positive disjoining pressure, independently of the viscosity ratio. The latter property is crucial for many microfluidic applications involving a collection of disperse droplets with a different viscosity from that of the continuum phase. As a preliminary application, the relative effective viscosity of a pressure-driven emulsion in a planar channel is computed

Severe cutaneous neoformations in animals caused by co-infection of orf virus and orthopoxvirus: A possible zoonosis?

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